LAUSR

Abstract In current times, variability and global climate change still require clarification of its effects on vegetation. The central issue in this discussion is how the distribution of fire foci can influence the vegetation cover pattern considering the spatial and temporal scales. Meteorological station data, together with Remote Sensing tools and Geographic Information Systems (GIS), produce very consistent results for monitoring the factors associated with the atmosphere – vegetation relationship. The present article aims to evaluate the relationship between occurrence of the fire foci and the Enhanced Vegetation Index (EVI) in the state of Rio de Janeiro (SRJ), during the period from January 2000 to December 2015. EVIs were obtained through analysis of the sensor images Moderate Resolution Imaging Spectroradiometer (MODIS), with spatial (250 m) and temporal (16 days) resolutions, during 15 years, taking into consideration the different forest typologies of the biome in Atlantic forest as well as the SRJ administrative divisions. After the organization of the time series of fire foci, the Kernel density (20 km) was calculated for each month, to design the circular neighborhood around the fire foci. Afterward, the EVIs were obtained through analysis of the images of the sensors mentioned above, considering the same temporal and spatial scales. The present study revealed the occurrence of more than 10,000 fire foci in SRJ. According to the Pettit test, the years 2000, 2013, 2014 and 2015 recorded the highest frequency of occurrences. The North and Metropolitan regions of SRJ had a higher frequency of the fire foci, especially in the Ombrophylous Dense Forest and Pioneer Formations. However, Ombrophylous Forests, Seasonal Forest and Pioneer Formation showed an increase in forest cover from 2000 to 2013. In light of observed relationships between fire foci and EVI, the convergence of approaches to fire foci and EVI can be an effective tool for planning and management of natural resources in the Atlantic Forest.